tylermorganwall

library(rayshader)
wave = matrix(0,200,200)

for(t in seq(1,360,1)) {
  for(i in 1:200) {
    for(j in 1:200) {
      wave[i,j] = 50*sinpi(sqrt((i-100)^2 + (j-100)^2)/30-t/180) * exp(-(sqrt((i-100)^2 + (j-100)^2))/100)
    }
  }
  wave %>% height_shade() %>% plot_3d(wave, soliddepth = -50, shadowdepth = -70, theta=315,zoom=1.1)

Zate

Freezer cgroup FTW

In a terminal start a server.

$ python -m SimpleHTTPServer 8000

In another terminal set up the cgroups freezer.

shahril96

import sys
import itertools
from z3 import *

#
# Original puzzle
#
'''
Five friends have their gardens next to one another, where they grow three kinds of crops:

danielecook

Calling Nim from R

A super short introduction how to call Nim code from R using the .C interface. I’m not an R user normally, so I googled and used this post as a reference: https://www.r-bloggers.com/three-ways-to-call-cc-from-r/

Writing our Nim procedure

Let’s define a simple procedure, which we want Nim to do:

sinkingsugar

import nimline
import os

static:
  let
    halideDist = getenv("HALIDE_DIST")
  
  assert halideDist != "" , "HALIDE_DIST environment variables not set!"

when defined windows:

sinkingsugar

FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04

RUN apt-get update && apt-get install -y build-essential git cmake python3-pip libmpfr-dev libgmp-dev wget curl

RUN pip3 install pyyaml
RUN pip3 install typing

RUN cd && \
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh

tdhopper

# http://editorconfig.org/#file-format-details
root = true

[*]
charset = utf-8
end_of_line = lf
indent_size = 4
indent_style = space
insert_final_newline = true
trim_trailing_whitespace = true

arsperger

cat data.csv | awk -F',' '{print " SET \""$1"\" \""$2"\" \n"}' | redis-cli --pipe 

joshlk

import pandas as pd

def _map_to_pandas(rdds):
    """ Needs to be here due to pickling issues """
    return [pd.DataFrame(list(rdds))]

def toPandas(df, n_partitions=None):
    """
    Returns the contents of `df` as a local `pandas.DataFrame` in a speedy fashion. The DataFrame is
    repartitioned if `n_partitions` is passed.

wbazant

Singularity container for an R module on a research cluster for VEuPathDB

Introduction

To use this technology, we need Singularity installed in the target environment by root, which is possibly the largest obstacle for us.

Writing a development container

Here is a container for analysing 16s rRNA data in MicrobiomeDB, requiring an R package DADA2. DADA2 releases to BioConductor, but we want the ability to load an arbitrary commit for development.

We can build on somebody's container with r-devtools, and add our libraries: